I have a big table(bo_sip_cti_event) which is too largest to even run queries on this so I made the same table (bo_sip_cti_event_day), added trigger after insert on bo_sip_cti_event to add all the same values to bo_sip_cti_event_day and now I am thinking if I significantly slowed down inserts into bo_sip_cti_event.
So generally, does trigger after insert slow down operations on this table?
Yes, the trigger must slow down inserts.
The reason is that relational databases are ACID compliant: All actions, including side-effects like triggers, must be completed before the update transaction completes. So triggers must be executed synchronously, and that consumes CPU, and in your case I/O too, which ultimately takes more time. There's no getting around it.
The answer is yes: it is additional overhead, so obviously it takes time to finish the transaction with the additional trigger execution.
Your design makes me wonder if:
You explored all options to speed up your large table. Even billions of rows can be handled quite fine, if you have proper index ect. But it all depends on the table, the design, the data and the queries.
What exactly your trigger is doing. The table name "_day" raises questions when and where and how exactly this table is cleaned out at midnight. Hopefully not inside the trigger function, and hopefully not with a "DELETE FROM".
Related
I plan to be batch inserting a large volume of rows into a Postgres table using the \copy command once per minute. My benchmarks show I should be able to insert about 40k rows per second, and I plan to do this for 3 or 4 seconds each minute.
Are read queries on the table blocked or impacted whilst the \copy dump is occurring? And I wonder the same for inserts as well?
I'm assuming as well that tables which aren't being \copy'd into will face no blocking issues.
The manual:
The main advantage of using the MVCC model of concurrency control
rather than locking is that in MVCC locks acquired for querying
(reading) data do not conflict with locks acquired for writing data,
and so reading never blocks writing and writing never blocks reading.
That's the beauty of the MVCC model used by Postgres.
So, no, readers are not blocked. Neither in the target table, nor in any other table.
Impacted? Well, bulk loading large amounts of data incurs considerable load on the system (especially I/O) which potentially impacts all other processes competing for the same resources. So if your system is already reaching some limits, readers may be impacted this way.
Rows written by your COPY command (by way of psql's \copy) are not visible to other transactions until the transaction is committed.
Concurrent INSERT commands are not blocked either - unless you have UNIQUE (or PK) constraints / indexes where writes do compete. Avoid race conditions with overlapping unique values! And performance can be impacted even with non-unique indexes as writing to indexes involves some short-term locking.
Generally, keep indexes on your table to a minimum if you plan huge bulk writes every minute. Every index incurs additional costs for the write - and may bloat more than the table if write patterns are unfavorable. Autovacuum may have a hard time to keep up.
I'm new with PostgreSQL and I would like to know or have some leads on:
Emit event (call an API) when a table is updated
My problem is: I have a SSO that insert row in an event table when user do something (login, register, update info). I need to exploit these inserts in another solution (a loyalty program) on real time.
For now I have in mind to query the table every minute (in nodeJS) and compare the size of table with the size of the previous minute. I think that is not the good way :)
You can do that with a trigger in principle. If the API is external to the database, you'd need a trigger function written in C or a language like PL/Perl or PL/Python that can perform the action you need.
However, unless this action can be guaranteed to be fast, it may not be a good idea to run it in a trigger. The trigger runs in the same transaction as the triggering statement, so if your trigger happens to run for a long time, you end up with a long database transaction. This has two main disadvantages:
Locks are held for a long time, which harms concurrency and hence performance, and also increases the risk of deadlocks.
Autovacuum cannot remove dead rows that were still active when the transaction started, which can lead to excessive table bloat on busy tables.
To avoid that risk, it is often better to use a queuing system: The trigger creates an entry in the queue, which is a fast action, and worker processes read and process these queue entries asynchronously outside the database.
Implementing a queue in a database is notoriously difficult, so you may want to look for existing solutions.
As per the documentation,
Loading large number of rows using COPY is always faster than using INSERT, even if PREPARE is used and multiple insertions are batched into a single transaction.
Why COPY is faster than INSERT (multiple insertion are batched into single transaction) ?
Quite a number of reasons, actually, but the main ones are:
Typically, client applications wait for confirmation of one INSERT's success before sending the next. So there's a round-trip delay for each INSERT, scheduling delays, etc. (PgJDBC supports pipelineing INSERTs in batches, but I'm not aware of any other clients that do).
Each INSERT has to go through the whole executor. Use of a prepared statement bypasses the need to run the parser, rewriter and planner, but there's still executor state to set up and tear down for each row. COPY does some setup once, and has an extremely low overhead for each row, especially where no triggers are involved.
The first point is the most significant. It's all about network round-trips and rescheduling delays.
This is because COPY is a single statement, while each INSERT is a separate statement. Since each single statement is normally subject to logging (manual), even inside a unique transaction, the use of many INSERT is slower than the use of a single COPY.
I have a table called deposits
When a deposit is made, the table is locked, so the query looks something like:
SELECT * FROM deposits WHERE id=123 FOR UPDATE
I assume FOR UPDATE is locking the table so that we can manipulate it without another thread stomping on the data.
The problem occurs though, when other deposits are trying to get the lock for the table. What happens is, somewhere in between locking the table and calling psql_commit() something is failing and keeping the lock for a stupidly long amount of time. There are a couple of things I need help addressing:
Subsequent queries trying to get the lock should fail, I have tried achieving this with NOWAIT but would prefer a timeout method (because it may be ok to wait, just not wait for a 'stupid amount of time')
Ideally I would head this off at the pass, and have my initial query only hold the lock for a certain amount of time, is this possible with postgresql?
Is there some other magic function I can tack onto the query (similar to NOWAIT) which will only wait for the lock for 4 seconds before failing?
Due to the painfully monolithic spaghetti code nature of the code base, its not simply a matter of changing global configs, it kinda needs to be a per-query based solution
Thanks for your help guys, I will keep poking around but I haven't had much luck. Is this a non-existing function of psql, because I found this: http://www.postgresql.org/message-id/40286F1F.8050703#optusnet.com.au
I assume FOR UPDATE is locking the table so that we can manipulate it without another thread stomping on the data.
Nope. FOR UPDATE locks only those rows, so that another transaction that attempts to lock them (with FOR SHARE, FOR UPDATE, UPDATE or DELETE) blocks until your transaction commits or rolls back.
If you want a whole table lock that blocks inserts/updates/deletes you probably want LOCK TABLE ... IN EXCLUSIVE MODE.
Subsequent queries trying to get the lock should fail, I have tried achieving this with NOWAIT but would prefer a timeout method (because it may be ok to wait, just not wait for a 'stupid amount of time')
See the lock_timeout setting. This was added in 9.3 and is not available in older versions.
Crude approximations for older versions can be achieved with statement_timeout, but that can lead to statements being cancelled unnecessarily. If statement_timeout is 1s and a statement waits 950ms on a lock, it might then get the lock and proceed, only to be immediately cancelled by a timeout. Not what you want.
There's no query-level way to set lock_timeout, but you can and should just:
SET LOCAL lock_timeout = '1s';
after you BEGIN a transaction.
Ideally I would head this off at the pass, and have my initial query only hold the lock for a certain amount of time, is this possible with postgresql?
There is a statement timeout, but locks are held at transaction level. There's no transaction timeout feature.
If you're running single-statement transactions you can just set a statement_timeout before running the statement to limit how long it can run for. This isn't quite the same thing as limiting how long it can hold a lock, though, because it might wait 900ms of an allowed 1s for the lock, only actually hold the lock for 100ms, then get cancelled by the timeout.
Is there some other magic function I can tack onto the query (similar to NOWAIT) which will only wait for the lock for 4 seconds before failing?
No. You must:
BEGIN;
SET LOCAL lock_timeout = '4s';
SELECT ....;
COMMIT;
Due to the painfully monolithic spaghetti code nature of the code base, its not simply a matter of changing global configs, it kinda needs to be a per-query based solution
SET LOCAL is suitable, and preferred, for this.
There's no way to do it in the text of the query, it must be a separate statement.
The mailing list post you linked to is a proposal for an imaginary syntax that was never implemented (at least in a public PostgreSQL release) and does not exist.
In a situation like this you may want to consider "optimistic concurrency control", often called "optimistic locking". It gives you greater control over locking behaviour at the cost of increased rates of query repetition and the need for more application logic.
I realize update operation speed in PostgreSQL doesn't meet my expectation especially when I update so many row at the same time, said 10K rows data. Is there any fast alternative to UPDATE? as using fast COPY to INSERT operation.
Thanks before.
Unlike INSERT, UPDATE can optimize for large writes. I have certainly had cases where I was updating tens of thousands of records and had it reasonably fast. The normal caveats for bulk operations apply, of course:
Indexing doesn't always help and in fact will not help if updating your entire table. You may find it faster to drop indexes, update, and recreate them.
NOT EXISTS is painfully slow in updates over large sets. Find a way of making things work with a left join instead.
If Normal performance rules apply (please look at query plans, etc).